Data currency is an important factor influencing the data quality. The reliability of data currency plays a critical role in data retrieval accuracy and data analysis credibility. Inaccurate data currency and outdated data bring many problems to the application of big data, which greatly affects the exertion of data value. For data that with imprecise time attribute or missing timestamp, exact repair of timestamp is often difficult, but it is possible to restore the currency orders according to specific currency based rules to meet various requirements in data cleaning and applications. Based on the analysis of data currency application requirements, this study first introduces the related concepts of data currency, defines attributes currency-based rules in formal method, and then proposes the currency rules discovery algorithm and the currency repair method. The algorithms efficiency and recovery effect are tested on real dataset, the factors that affect accuracy of the algorithms are analyzed. Experimental results show that the proposed methods are efficient and effective.